Writer Recognition Using Off-line Handwritten Single Block Characters
Adrian Leo Hagstr\"om, Rustam Stanikzai, Josef Bigun, Fernando, Alonso-Fernandez

TL;DR
This study demonstrates that individual handwritten digits, specifically date of birth, contain biometric information that can be used for writer recognition, achieving high accuracy with deep learning methods on a small dataset.
Contribution
It introduces a novel approach to writer recognition using off-line handwritten digits, comparing handcrafted and deep features, and evaluates performance with limited enrollment samples.
Findings
Deep features achieve 94% Top-1 accuracy with ten enrollment samples.
Biometric information is present in just six handwritten digits.
Recognition performance improves with more enrollment samples.
Abstract
Block characters are often used when filling paper forms for a variety of purposes. We investigate if there is biometric information contained within individual digits of handwritten text. In particular, we use personal identity numbers consisting of the six digits of the date of birth, DoB. We evaluate two recognition approaches, one based on handcrafted features that compute contour directional measurements, and another based on deep features from a ResNet50 model. We use a self-captured database of 317 individuals and 4920 written DoBs in total. Results show the presence of identity-related information in a piece of handwritten information as small as six digits with the DoB. We also analyze the impact of the amount of enrolment samples, varying its number between one and ten. Results with such small amount of data are promising. With ten enrolment samples, the Top-1 accuracy with…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsHandwritten Text Recognition Techniques · Image Processing and 3D Reconstruction
